Descriptive Title: Severe and fatal traffic injuries per 100 road miles, annually

Geographic Unit of Analysis: Intersection and planning neighborhood

Severe and fatal traffic injuries (2008-2012)
NeighborhoodTotal Road MilesSevere/Fatal Injury CountTotal Injuries per 100 Road Miles, AnnuallyPedestrian Injury CountPedestrian Injuries per 100 Road Miles, AnnuallyCyclist Injury CountCyclist Injuries per 100 Road Miles, AnnuallyDriver/Passenger Injury CountDriver/Passenger Injuries per 100 Road Miles, Annually% Road Miles that are HICs
Bayview/Hunter's Point 96 56 12 15 3 5 1 36 7 5%
Bernal Heights 45 29 13 9 4 6 3 14 6 9%
Castro/Upper Market 29 33 23 15 11 8 6 10 7 19%
Chinatown 12 19 32 10 17 3 5 6 10 19%
Excelsior 43 35 16 15 7 2 1 18 8 8%
Financial District/South Beach 39 78 40 32 16 16 8 30 15 30%
Glen Park 19 3 3 1 1 0 0 2 2 1%
Golden Gate Park 30 43 29 14 9 4 3 25 17 25%
Haight Ashbury 18 16 18 4 4 9 10 3 3 17%
Hayes Valley 18 30 34 7 8 8 9 15 17 24%
Inner Richmond 22 23 21 9 8 2 2 12 11 12%
Inner Sunset 37 19 10 11 6 2 1 6 3 5%
Japantown 5 8 31 4 16 2 8 2 8 30%
Lakeshore 26 28 21 7 5 3 2 18 14 17%
Lincoln Park 4 0 0 0 0 0 0 0 0 0%
Lone Mountain/USF 18 26 30 13 15 7 8 6 7 18%
Marina 29 30 21 18 13 0 0 12 8 9%
McLaren Park 7 2 6 0 0 0 0 2 6 2%
Mission 64 133 42 46 14 37 12 50 16 28%
Mission Bay 23 21 18 8 7 1 1 12 11 12%
Nob Hill 16 30 37 21 26 0 0 9 11 37%
Noe Valley 31 11 7 4 3 0 0 7 5 1%
North Beach 15 10 13 7 9 2 3 1 1 10%
Oceanview/Merced/Ingleside 34 33 20 13 8 2 1 18 11 7%
Outer Mission 41 34 17 15 7 4 2 15 7 15%
Outer Richmond 45 35 15 15 7 2 1 18 8 10%
Pacific Heights 24 15 13 4 3 3 3 8 7 11%
Portola 36 21 12 7 4 1 1 13 7 7%
Potrero Hill 37 25 14 4 2 2 1 19 10 3%
Presidio 45 1 0 0 0 0 0 1 0 0%
Presidio Heights 17 15 18 4 5 0 0 11 13 11%
Russian Hill 18 13 15 5 6 4 4 4 4 11%
San Francisco 1,117 1,143 20 473 8 176 3 494 9 12%
Seacliff 9 1 2 0 0 1 2 0 0 0%
South of Market 36 84 47 49 28 9 5 26 15 30%
Sunset/Parkside 107 44 8 18 3 4 1 22 4 8%
Tenderloin 14 62 86 36 50 11 15 15 21 82%
Treasure Island 24 2 2 1 1 0 0 1 1 0%
Twin Peaks 18 5 5 2 2 1 1 2 2 0%
Visitacion Valley 20 8 8 6 6 1 1 1 1 1%
West of Twin Peaks 91 28 6 9 2 8 2 11 2 4%
Western Addition 20 34 35 15 15 6 6 13 13 43%

Why Is This An Indicator Of Health and Sustainability?

The annual rate of fatalities and severe injuries per 100 miles of street sustained from traffic collisions is an indicator of the safety risk of the street network for road users, including pedestrians, cyclists, drivers and passengers.  Traffic collisions involving motor vehicles are one of the leading causes of preventable injury in San Francisco, the nation, and the world,a and the leading cause of death in the United States for people aged 5-34.b  As area-level vehicle miles traveled and traffic volumes increase, so do traffic casualties.c  Speed is the other main contributing factor to injury severity – with higher speeds allowing for less driver reaction time and increased force when collisions occur.d  Vehicle speed has particularly profound impacts on more vulnerable road users, including pedestrians and cyclists.  Small increases in impact speed translate into large increases in fatality risks – for example, it has been estimated that the risk of pedestrian fatality is six times that at 30 mph relative to 20 mph.e  In addition to targeted enforcement efforts, planning and design decisions that reduce traffic volumes, speeds, and the need to drive, while promoting more walkable, safe environments include: traffic calming, street and intersection engineering countermeasures, transportation-land use planning coordination, and other transportation demand management measures such as road pricing.f  The injuries and deaths suffered in these collisions, as well as high medical and social costs, reflect a need for transportation safety practices, projects and policies to be integrated into all relevant agency agendas and across all levels of government to prevent injuries.g

Interpretation and Geographic Equity Analysis

For every 100 miles in San Francisco, there are approximately 20 total fatalities and severe injuries each year.  The eastern neighborhoods of the city have disproportionately higher rates of total severe injuries and fatalities associated with the presence of Highway 280 and 101 and higher traffic volumes and speeds on those roadways and nearby streets – as well as higher residential and employee densities.  Each of these neighborhoods has 2-4.3 times as many fatal/severe injuries per 100 road miles as the San Francisco’s citywide rate (see table). 

Severe/fatal cyclist injuries are largely concentrated in the Tenderloin, the Mission, Haight Ashbury and Haight Ashbury – where vehicle and cyclist volumes converge, often on busy arterials.  Severe/fatal pedestrian injuries are more concentrated in San Francisco’s downtown – including the Tenderloin, South of Market, ans Nob Hill neighborhoods – where there are higher volumes of traffic as well pedestrians (both residents and workers) along with higher traffic speeds on arterial streets in those communities.  It was found in 2010 by the Department of Public Health that 50% of injuries, as well as 55% of severe injuries and fatalities, occur on just 5% of San Francisco’s streets.  For more information about high-injury corridors in San Francisco, visit: http://www.sfhealthequity.org/elements/21-elements/transportation/137-pedestrian-safety.

Methods

Using ESRI ArcMap 10.1, the 2008 to 2012 tabular SWITRS collision level data (see data sources) of severe and fatal vehicle-to-vehicle, vehicle-to-pedestrian, and vehicle- to bicyclist collisions were geocoded to the nearest intersection by the San Francisco Department of Public Health.  Severe and fatal injuries in these collisions were then totaled per intersection and injury type.  Neighborhood severe and fatal injuries per 100 miles per year in total and for each injury type was calculated by obtaining the average injury count per year per neighborhood, dividing by the sum of the total street length per neighborhood, and then standardizing the estimate by multiplying by 100 miles – or more simply: ((Injuries/5 years)*100) / (Road Miles). 

Limitations

Injuries were geocoded to the nearest intersection based on data on primary and secondary streets as reported in SWITRS (see data sources).  Planning neighborhoods are delineated by streets, often major arterials, which tend to have higher rates of vehicle collisions.  This becomes a limitation for collisions that occurred on the border of two areas and need to be assigned to a planning neighborhood.  For example, the boundaries of the Golden Gate Park neighborhood result in the injuries that occur on roads on the periphery of the park being counted in that neighborhood total – which may be somewhat misleading if that total is interpreted as only including injuries that occur within the park. 

SWITRS data (see data sources) includes collisions on a public roadway that are reported to the California Highway Patrol.  However, some collisions go unreported for a number of reasons.  For example, neighborhoods with higher immigrant densities may have lower reporting rates because of fear of deportation, whereas neighborhoods with a strong community police presence may be more likely to report collisions.  However, it is notable that this indicator reflects severe injuries and fatalities – which given their serious implications are less susceptible to under-reporting to the police.

Data Source

The California Highway Patrol defines "motor vehicle" as a mechanically or electrically powered device not operated on rails, upon which or by which any person or property may be transported or drawn upon a roadway. This would include motorized bicycles (mopeds).

Tabular collision data was received from the California Highway Patrol, Statewide Integrated Traffic Records System (SWITRS) for 2008 to 2012. More information can be found at: http://www.chp.ca.gov/switrs/

Map and table prepared by City and County of San Francisco, Department of Public Health, Environmental Health Section using ArcGIS software.

Map data is presented at the level of the analysis neighborhood and street segment.

Table data is presented by analysis neighborhood.

Detailed information regarding census data, geographic units of analysis, their definitions, and their boundaries can be found at the following links:

Interactive boundaries map

http://sfindicatorproject.org/resources/data_map_methods

  1. WHO (World Health Organization), 2011a. United Nations Road Safety Collaboration: World unites to halt death and injury on the road. Available from: http://www.who.int/roadsafety/en.

  2. Centers for Disease Control and Prevention. 2010. WISQARS (Web-based Injury Statistics Query and Reporting System). Atlanta, GA: US Department of Health and Human Services, CDC. Available at http://www.cdc.gov/injury/wisqars.

  3. Ewing R, Dumbaugh E. 2009. The Built Environment and Traffic Safety : A Review of Empirical Evidence. Journal of Planning Literature 23: 347-367.

  4. Ewing R, Dumbaugh E. 2009. The Built Environment and Traffic Safety : A Review of Empirical Evidence. Journal of Planning Literature 23: 347-367.

  5. Richards, D.C., 2010. Relationship between Speed and Risk of Fatal Injury: Pedestrians and Car Occupants. Transportation Research Laboratory. Road Safety Web Publication No. 16. Department for Transport: London, UK.

  6. Victoria Transport Policy Institute. 2011. Online TDM Encyclopedia.  Available at: http://www.vtpi.org/tdm/

  7. PolicyLink, Prevention Institute, the Convergence Partnership. 2009. Cohen, Larry, Janani Srikantharajahm Leslie Mikkelsen. Equitable Transportation Policy, Recommendations and Research: Traffic Injury Prevention: A 21st-Century Approach.  131- 145. http://www.convergencepartnership.org/atf/cf/%7B245a9b44-6ded-4abd-a392-ae583809e350%7D/HEALTHTRANS_FULLBOOK_FINAL.PDF